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Application of Internal Model and Self-Adaptive PSD Controller in the Main Steam Temperature System
Authors: Li Shen; Luan-Ying Zhang; Jun-Jie Gu;
Abstract
In view of large time delay and uncertainty of the main steam temperature system in a power plant, combining with internal model controller, a control method based on adaptive PSD is proposed. The advanced control algorithms have the advantages of the simple algorithm and the small calculating amount. Compared with the conventional cascade PID control system, the simulation results show that the self-adaptive PSD control system has better control performance on adaptability, such as to decrease the overshoot, shorten the settling time, accelerate the response, etc.
Related Organizations
- North China Electric Power University China (People's Republic of)
- North China Electric Power University China (People's Republic of)
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).4 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average

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citations
Citations provided by BIP!
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
popularity
Popularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
4
Average
Average
Average